Triple
T1030826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kettering University |
E22245
|
entity |
| Predicate | hasStudentWorkRequirement |
P14667
|
FINISHED |
| Object | industry co-op placement |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: industry co-op placement | Statement: [Kettering University, hasStudentWorkRequirement, industry co-op placement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentWorkRequirement Context triple: [Kettering University, hasStudentWorkRequirement, industry co-op placement]
-
A.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
-
B.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
C.
requiresEducation
Indicates that performing or holding the related role, activity, or position depends on having a specified level or type of education.
-
D.
workRequirement
chosen
Indicates that one entity imposes or specifies a condition related to work that another entity must fulfill.
-
E.
hasWorkAsSubject
Indicates that an entity serves as the subject (creator or originator) of a particular work or creative output.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b95d35888190a20593a278175df7 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b7276180819085c6b23501a6a6e0 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.